Analytic Integration: The Next Step in Business Evolution

The Current Challenge for Organizational Progress

The next chapter in the history of business is focused on
the integration of analytics into all facets of corporate
life. Analytics isn't about massing data, and analytics is
not "reporting." It's the work of leveraging applied
statistics to develop the underpinnings of effective
measurable strategies. This applies to all industries.
This applies to all functional areas. Examples include
anything from how we abate risk in consumer finance, to how
we route calls in a call center. It could include how we
create a realistic financial forecast, or how we customize
point-of-sale promotions within analytically-derived
sub-chains of a retail chain.

This evolution is happening as there is an unavoidable
reality that if you are looking at any business opportunity,
the fusion of good data/predictive analytics/good
intuition/experience will outperform good
intuition/experience alone. To further explain, intuition
and experience may develop strong business strategies based
on the correct and proven belief that consumer demand is
driven by each consumer's:

■Recency of last purchase

■Number of past purchases

■Dollar value of purchases

This intuition and experientially based strategy may segment
customers on these three factors and develop customized
treatments to each segment.

The analytic approach would improve on the example above by
accurately attaching quantified value to each of these three
variables (what is the percent contribution of each of the
three factors to consumer demand?). Further, through
analytics we can develop, evaluate and manage ratios among
all of the variables and conduct mathematical exercises to
tease out additional information. Beyond that, hundreds
more variables can be easily explored to see if they add
value as well. Best of all, the final product won't be
groups of customers, but rather a ranking of each individual
customer. A parsimonious solution that is more robust and
more easily managed as compared to the business as usual
process.

The 3-variable intuitive/experiential strategy in this
example is profitable and proven. But, merging additional
data and deep strategic analytics to this example (and, in
fact, to all that we know today) can measurably take a
business' strategies and tactics to the next level.

To actively design organizations that will thrive in this
new environment try to objectively assess your current
organization for individuals that play on both sides of the
qualitative/quantitative fence. If these individuals are
available, carefully plan where they can be strategically
placed to gain immediate value (A key project? A functional
area facing a specific challenge?).

If you need to hire externally for individuals with these
skills, and your organization has no senior colleagues with
these backgrounds, strongly consider retaining consultants
with qualitative and analytic backgrounds and project
experience to be on your search committee. There are
endless stories of organizations who have built new
sophisticated data warehouses (some great - some not so
great). These organizations then assembled interview panels
comprised of qualitative business people and Information
Technologists to seek out and hire the talent that could
mine the data and build the strategies. A key flaw in this
hiring process is obvious.

"Decision Scientists" are the quantitative/qualitative
individuals that are responsible for making the data
warehouse pay off. If there are currently no Decision
Scientists in your organization, it is not likely that you
can effectively identify this talent. If, as an example,
you only speak English, you will not be very qualified to
hire a professional foreign language translator. Similarly,
if you haven't been responsible for developing business
strategies that have strong advanced analytic underpinnings,
you will be at a major disadvantage in identifying (let alone
developing) appropriate key talent.

That said, your hiring committee will be seeking out
individuals that have managed to merge their analytic and
traditional business skills. These are people that can
clearly demonstrate this ability via detailed "case study"
examples that review all facets of a project (e.g., for a
direct mail campaign, clarity should be gained on the
individual's contribution in all project phases, from
computer coding that led to a targeting strategy all the way
through final creative development). Ask questions that will
allow your prospective candidates to showcase their
step-by-step analytic, strategy development, and operational
skills. And, as with any candidate, these individuals should
also display well-developed interpersonal and communication
skills (the strategy will have no value if you cannot sell
it into the business and provide clear instructions relative
to its use). In short, an ideal candidate will have the
ability to easily understand and embrace the "big picture"
and the logic and value of what-is...prior to merging in the
quantitative rigor needed to develop what-is-next.

Once your team is staffed, they will likely face a number of
common challenges. Not the least of which is having the
company accept resulting strategies for testing.
Interestingly, I have found that the likelihood of an
organization to embrace analytically-based strategies is
inversely proportional to the level of fear that pervades
the organization. The fear can be related to the loss of a
job, fiefdom, responsibility...or just the perceived loss of
stature that results from having an individual from the
"outside" find improvement opportunities.

It will be incumbent on your new, well-diversified,
analytically-talented and qualitatively astute team to
present themselves as internal consultants (...individuals
who will only look good if the client looks good). It will
also be incumbent on senior management to actively support
the responsible testing of promising new ideas.

It is important to build a strong culture of testing in your
organization. Have a bias in favor of testing. Manage the
tests so that the financial liability is minimized, but so
that the results are still statistically valid within a
published margin of error. As a centerpiece of this testing
culture, underscore that all work needs to be quantified, and
that all test results (positive or negative) are wins for the
business. By continuing to learn, we continue to improve.

About the Author:

This article was written by Alan Gorenstein.